When it comes to AI, we’re all too familiar with sci-fi dystopian narratives hyping up the ultimate showdown of survival between humans and machines. The problem is not the rise of machines, but our limited perception. We mistakenly perceive AI as humanity’s evolutionary competitors rather than our technological companions.
In a data-driven work culture with real-time decision making, precision is critical and workers are challenged by the ever-increasing data volumes that they have to process.
Dull data processing - repetitive, mechanical jobs that may be handled by humans but have nothing humane to offer - not only inhibits people from doing the valuable work they were hired for but have mental implications ranging from dissatisfaction to burnout. As a result, productivity is taking a hit and employee turnover will likely rise in organizations that refuse to adopt automation to minimize drudgery and amplify creativity.
Automation is the need of the hour. It is only intended to empower, not endanger the future of our workforce. You can’t turn a blind eye to the sheer efficiency, agility, and adaptability that automation promises and delivers for your business.
Yet, the question on every worker’s mind is – “Will my job be soon replaced by a robot?”
Let's take the ATM as an example. If you had to bet on a technology that would surely displace a ton of banking jobs, the automated teller machine would have been a safe bet.
Yet, the banking industry employs more tellers now than before ATMs were ever introduced. Why? It's because ATMs greatly lowered the expenditure of opening bank branches. As a result, banks were able to open many more branches, which led to more employment for human tellers.
Many job descriptions will change. But the innovation intersection of automation, AI, and robotics will manifest some of the greatest job opportunities in our generation.
Like the previous revolutions, it will certainly boost productivity. However, while previous revolutions led to more specialized and repetitive work, the AI revolution will enable us to place the focus back on our human strengths like creativity and strategic thinking to accomplish more satisfying tasks.
Gazing into the job market crystal ball: What the future holds
According to a 2018 WEF report on the future of jobs, the rise of artificial intelligence will create 60 million net new jobs by 2022. This net positive job growth will also usher in a significant shift in the quality, location, and security of these new roles.
Have you ever considered that if a job can be completely taken over by a robot, then it may not be a good job for a human in the first place? Or why climbing the promotional ladder in our organizations is often defined by the ratio of strategic tasks to repetitive, mechanical tasks? The old organizational hierarchy involves paying your dues through hard, tedious work just to rise the food chain and apply your brain.
What automation offers us is a lifeline out of this crippled system and the ability to focus on our strengths early-on. The time has come to shift our conversation towards evaluating the kind of work we, as humans, are best at, and how we can leverage AI to enhance our productivity while making our work more satisfying.
A report conducted by Gartner shared that by 2022, one in five workers engaged in non-routine tasks will depend on AI to do their work. They projected that the best way to maximize the value of the automation revolution is a collaborative model that combines human and artificial intelligence.
Such an approach would benefit workers in all types of jobs, from entry-level to those that require management-level decision making. The prerequisite is that people are embracing human-machine collaboration and restructure tasks accordingly.
So instead of worrying about a job market apocalypse that phases out all traditional skills, it’s more important to understand how it will lead to new and more satisfying opportunities along with the development of future skills.
Think job upgrades, not job replacements
The notion of continuous learning and the emphasis on critical thinking will pick up more momentum as machines take over all standardized operations. On the other hand, humans will finally invest more time and energy doing the work they love.
In the future, job roles will not just be limited to a single skill - this is what machines excel at. People should focus on a combination of skills and improve their capabilities to make decisions based on the bigger picture.
It’s important to understand that AI doesn’t automate jobs. It automates certain tasks within these jobs and thereby offers opportunities to focus on ones that require vision, connection, and empathy.
But what are the skills needed to harness the opportunities that AI offers? Human skills can be grouped into three core categories based on their preparation for automation:
1. Process-based skills
Process-based skills apply to any mechanical or repetitive activities done within a very structured and predictable framework. Presently, these activities account for almost half of the daily activities of your workforce. They include everything from manufacturing items, accounting processes, customer on-boarding, fraud identification, filing documents, etc.
Over the next decade, at least 80% of process-oriented tasks will be taken over by AI systems. Most process-oriented tasks will be executed by machines instead of humans.
Human jobs will be geared towards managing and troubleshooting these AI tools to further refine productivity. In practice, controlling AI automation works by defining confidence level boundaries and placing a human in the loop.
For instance, with the widespread introduction of self-checkout systems in supermarkets, human cashiers are now playing the roles of checkout assistants. They help troubleshoot the self-checkout machines and answer specific customer queries to retain the personalized touch.
AI works similarly for business processes. While it streamlines operations, it also provides the opportunity to put a particular focus on specific tasks where a personal touch can be a great value-add.
2. Quantitative Reasoning Skills
When it comes to data crunching and simple data processing, machines are unbeatable. You can also implement machine learning algorithms to automate tasks with unstructured data.
A Harvard research study confirmed the power of human-machine collaboration for tasks that require quantitative reasoning skills. It revealed how AI algorithms used by a medical professional can identify diagnostic scans with 92% accuracy. Humans do slightly better with 96% accuracy. However, when they took the collaborative approach, the accuracy of diagnosis crossed 99%!
Quantitative reasoning tasks are projected to have a 50-50% distribution between humans and machines in the job market as automation evolves.
Here are some interesting new jobs that may pop up thanks to this domain:
- AI interaction designers - to communicate with team members for translating requests into machine functions
- Simplicity consultants – to remove redundancies and streamline processes and technologies in your organization
- Well-being coaches – to oversee a healthy shift in management policy between machines and humans to boost the collaborative effect
- Analytic HRs – to leverage (AI-based) analytics for identifying talent and improving talent management strategies
3. Cross-functional reasoning skills
Once the automation of jobs that demand process-oriented and quantitative skills has reached a significant degree, AI will free us to climb up our skillset ladder to exercise cross-functional reasoning skills. In other words, free us to pursue creative and social abilities, which reflect the core of the human spirit that is (currently) inimitable.
It includes tasks involving complex interpretation, creating designs, planning strategies, managing people, resolving conflicts, and more.
For example, an AI chatbot can be programmed to answer approximately 80% of queries. This frees human customer service representatives to handle the other 20% that demand more contextual understanding.
Here are some of the most popular jobs involving cross-functional reasoning skills on the horizon:
- Recruitment specialists: Assemble short-term freelance teams to complete highly specific projects
- Insight enablers: Help your company tap into the insights hidden in your wealth of data
- Freelance professors: Oversee in-house skill training to guarantee your organization’s continuous learning process goes smoothly
- User interaction specialists: Enabling rich customer experiences and drive up customer loyalty
These job roles will be automation-powered, but not automation-dependant as humans will continue to dominate over 80% of cross-functional reasoning tasks.
The two leading forces behind the renewed explosion of creativity and fulfillment in the job market triggered by AI will be:
- Reducing our cognitive load - the amount of information in our working memory - by delegating repetitive and deterministic processes to automation tools. The lower your cognitive load, the greater your creative output and overall feeling of fulfillment.
- A shift from predictive to prescriptive intelligence. Armed with clearer insights and context to our customer engagement due to automation tools, we now have a much better understanding of the "why" behind the data. Rather than just telling customers what they should do, sales workers, for example, can place their focus on why it's in their best interest to do so - and this will empower your workforce. While robots take the lead on filtering and pre-qualifying leads, your sales teams focus on personalizing their messaging for high-quality leads to deliver what resonates with each customer and maximizes engagement.
A research study conducted by Fortune showed that there are 4 key components to a satisfying job:
- A job that truly tests our abilities
- Allows us to progress steadily
- Gives us more autonomy
- Fosters a sense of belonging
Automation will help inject more agility, transparency, productivity, and creativity into organizations while minimizing drudgery. It’s clear, the next foot forward is towards a collaborative human-machine economy where re-skilling and up-skilling of the workforce will become the prime focus.
At the end of it all, we’ll remember AI for the humanity it restored to our jobs rather than the jobs it took from us.